In my previous article, we explored how academia and the private sector are building Canadian expertise in artificial intelligence. What is the role of the Canadian government, and what should it be?

Examples of Canadian AI leadership include the University of Toronto, where students have developed a diagnostic robot for the elderly, and Purple Forge Corp., a startup using AI to help residents obtain municipal services.

However, the biggest variable for artificial intelligence in Canada is the public sector. Besides a few scattered initiatives, the Canadian government is falling short. This offers lessons for other nations and regions hoping to promote AI and robotics.

Setting priorities with the Canadian government

In 2007, the Canadian government unveiled a science and technology strategy. In the following years, it updated this strategy with new “research priorities.” In 2014, Canada added advanced manufacturing as a priority. This included, among other things, robotics through automation and nanotechnology.

In 2008, Canada’s government unveiled a $250 million fund for research and development in the automotive sector. In 2014, the government put another $500 million into the fund. One focus of this fund is robotics. AI for the Canadian automotive industry could be a byproduct of this innovation fund.

In March 2016, the Canadian Parking Association published an article on AI-enabled “robotic vehicles” and their impact on the parking industry. Several robotics technologies were mentioned, such as autonomous aerial vehicles monitoring security vulnerabilities, maintenance robots cleaning roads and sidewalks, and the use of AI to identify patterns and threats from the data these robots are transmitting.

The Canadian Parking Association has studied intelligent vehicles.

Can such organizations lobby the Canadian government to help implement some of these AI applications?

The Information and Communications Technology Council (ICTC), a Canadian nonprofit, published a report on fostering “digital talent” in Canada through 2020. The report mentioned automation, with specific references to robotics, AI, and deep learning.

Automation was listed as one of four “technology drivers” that are expected to grow the Canadian economy in the coming years. The report also mentioned that industrial automation is a $2 billion market in Canada.

Although the Canadian government has clearly supported industrial automation in the automotive industry, it is lagging when it comes to formulating a proper strategy for AI. It should take heed from public-sector organizations like the ICTC.

In addition, Canada faces several challenges to becoming a global AI power.

Canadian AI challenges

The first and biggest AI challenge is the loss of Canadian talent to the U.S. Over the past several years, Canadian AI experts have been recruited by American companies such as Google and institutions like Carnegie Mellon University.

At the same time, Canadian AI firms are being bought up by foreign technology giants. One example is DNNresearch, a startup focused on image recognition that Google bought in 2013.

Without a sound strategy, the exodus of Canadian artificial intelligence and machine learning talent is likely to continue.

Canada’s federal and provincial government could slow this by providing AI companies and startups with innovative funding schemes, lowering taxes, or providing access to resources like shared workspaces. Such a program could also be used to attract AI from other countries into Canada (or back to Canada in the case of the U.S.).

The second challenge is that the Canadian government has no real strategy or plan for artificial intelligence. There is no five-year plan like in China or a $840 million AI fund like in South Korea. Instead, Canada is relying on scattered government strategies/grants and initiatives from the private sector to sustain its AI growth.

The part of the study that focused on “awareness, innovation, agility, and the ability to channel resources” gave poor marks to 35 percent of Canadian companies. If these companies don’t view robotics in the same way as companies from other countries, it could create a huge deficit in Canada’s AI landscape.

The fourth and final challenge for Canadian AI is that its innovations fall short when measured up against those from other countries. For example, South Korea’s Exobrain is meant to take on IBM Watson from the U.S.

In Mexico, scientists have created an AI-enabled walker to help the disabled. It was designed from the ground up to crunch data and make adjustments in real time based on what the user is doing.

During the 2016 Annual International Conference on Biologically Inspired Cognitive Architectures in New York, a Russian professor revealed that Russia was “on the verge” of developing AI that could feel human emotions. Compared with these advances, Canada’s AI industry appears to still be in its early stages.

Points of light

Canada has several bright spots for artificial intelligence and robotics. Academia remains a dominant force, and several companies are developing or partnering to create new products.

But these bright spots are scattered across the country. They are not connected by any unique Canadian government strategy or private-sector blueprint. Without a support system, these bright spots risk remaining just that — spots, with no real ability to grow within Canada or to other parts of the world.

And compared with efforts in other countries, Canada still has a lot of catching up to do.

When a Canadian AI innovation make waves, it attracts attention, resulting in a foreign company acquiring the organization and the talent that comes with it.

For Canada to be a global AI leader, the Canadian government and large companies must deploy a new strategy and do it fast. It needs a strategy to compete in the global AI race. This race has already started, and Canada appears to still be waiting for the gun to fire.

Abishur Prakash is a geopolitical futurist and author focused on how new technologies, such as AI, blockchain, gene editing, and virtual reality will transform geopolitics. He works at Center for Innovating the Future, a strategy innovation lab in Toronto. Prakash advises multinationals, governments, and startups. He is the author of three books: Next Geopolitics, Vols. 1 and 2, and Go.AI (Geopolitics of Artificial Intelligence). In addition to RBR, Prakash's work has been published in Forbes, Scientific American, and Newsweek.